Volatility Puzzle: Long Memory or Antipersistency
The log realized volatility (RV) is often modeled as an autoregressive fractionally integrated moving average model ARFIMA(1, d, 0). Two conflicting empirical results have been found in the literature. One stream shows that log RV has a long memory (i.e., the fractional parameter d > 0). The othe...
Saved in:
Main Authors: | , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/soe_research/2693 https://ink.library.smu.edu.sg/context/soe_research/article/3692/viewcontent/VolatilityPuzzle_sv.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.soe_research-3692 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.soe_research-36922023-11-10T02:53:46Z Volatility Puzzle: Long Memory or Antipersistency SHI, Shuping Jun YU, The log realized volatility (RV) is often modeled as an autoregressive fractionally integrated moving average model ARFIMA(1, d, 0). Two conflicting empirical results have been found in the literature. One stream shows that log RV has a long memory (i.e., the fractional parameter d > 0). The other stream suggests that the autoregressive coefficient α is near unity with antipersistent errors (i.e., d 2023-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2693 info:doi/10.1287/mnsc.2022.4552 https://ink.library.smu.edu.sg/context/soe_research/article/3692/viewcontent/VolatilityPuzzle_sv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Fractional integration Long memory Realized volatility Roughness Short-run dynamics Econometrics |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
Fractional integration Long memory Realized volatility Roughness Short-run dynamics Econometrics |
spellingShingle |
Fractional integration Long memory Realized volatility Roughness Short-run dynamics Econometrics SHI, Shuping Jun YU, Volatility Puzzle: Long Memory or Antipersistency |
description |
The log realized volatility (RV) is often modeled as an autoregressive fractionally integrated moving average model ARFIMA(1, d, 0). Two conflicting empirical results have been found in the literature. One stream shows that log RV has a long memory (i.e., the fractional parameter d > 0). The other stream suggests that the autoregressive coefficient α is near unity with antipersistent errors (i.e., d |
format |
text |
author |
SHI, Shuping Jun YU, |
author_facet |
SHI, Shuping Jun YU, |
author_sort |
SHI, Shuping |
title |
Volatility Puzzle: Long Memory or Antipersistency |
title_short |
Volatility Puzzle: Long Memory or Antipersistency |
title_full |
Volatility Puzzle: Long Memory or Antipersistency |
title_fullStr |
Volatility Puzzle: Long Memory or Antipersistency |
title_full_unstemmed |
Volatility Puzzle: Long Memory or Antipersistency |
title_sort |
volatility puzzle: long memory or antipersistency |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2023 |
url |
https://ink.library.smu.edu.sg/soe_research/2693 https://ink.library.smu.edu.sg/context/soe_research/article/3692/viewcontent/VolatilityPuzzle_sv.pdf |
_version_ |
1783955667968589824 |